Performance Comparison through Simulations
Last updated: 2019-07-04
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Knit directory: diffNet/
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Simulate X
n = 30
X = scale(rnorm(n)) * sqrt(n) / sqrt(n-1)
X = cbind(rep(1, n), X)
B = 1000Generate \(\rho\) using tanh function
power = c("LM", "LA", "Fisher")
for (a in c(0, 0.5, 1, 1.5, 2)){
if(a==0){
rho = runif(1,-1,1)
}
else{
alpha = c(0, a)
rho = h1_fisher(X, alpha)
}
out = do_sim(X = X, n = n, B = B, rho = rho, mles = TRUE)
# save(out, file = paste0("simulation_n30_fisher_", a, ".RData"))
power = cbind(power, powercheck(out, B = B, n = a)[,2])
}
print(power) power
[1,] "LM" "0.052" "0.206" "0.542" "0.795" "0.91"
[2,] "LA" "0.054" "0.18" "0.511" "0.722" "0.828"
[3,] "Fisher" "0.046" "0.247" "0.693" "0.965" "0.992"newX = cbind(rep(1, 1000), sort(runif(1000, -2.5, 2.5)))
df = data.frame(alpha1 = h1_fisher(newX, c(0,0.5)),
alpha2 = h1_fisher(newX, c(0,1)),
alpha3 = h1_fisher(newX, c(0,1.5)),
alpha4 = h1_fisher(newX, c(0,2)))
df = melt(df)No id variables; using all as measure variablesdf$X = rep(newX[,2], 4)
levels(df$variable) = c("0.5", "1", "1.5", "2")
colnames(df)[1] = "alpha"
ggplot(df, aes(x = X, y = value, col = alpha)) + geom_line() + labs(color=expression(alpha)) +
ylab(expression(rho)) +
xlab(expression(X)) +
theme_bw(base_size=12)+
ggtitle("tanh")
ggsave("fisher.png", height = 3, width = 3)Generate \(\rho\) using quadratic function
power = c("LM", "LA", "Fisher")
for (a in c(0.2, 0.3, 0.4, 0.5)){
if(a==0){
rho = runif(1,-1,1)
}
else{
alpha = c(0, a)
rho = h6_quadratic(X, alpha)
rho = pmin(0.99, rho); rho = pmax(-0.99, rho)
}
out = do_sim(X = X, n = n, B = B, rho = rho, mles = TRUE)
# save(out, file = paste0("simulation_n30_sin_", a, ".RData"))
power = cbind(power, powercheck(out, B = B, n = a)[,2])
}
print(power) power
[1,] "LM" "0.627" "0.587" "0.539" "0.531"
[2,] "LA" "0.042" "0.047" "0.058" "0.079"
[3,] "Fisher" "0.533" "0.438" "0.371" "0.338"newX = cbind(rep(1, 1000), sort(runif(1000, -2.5, 2.5)))
df = data.frame(alpha1 = h6_quadratic(newX, c(0,0.2)),
alpha2 = h6_quadratic(newX, c(0,0.3)),
alpha3 = h6_quadratic(newX, c(0,0.4)),
alpha4 = h6_quadratic(newX, c(0,0.5)))
df = melt(df)No id variables; using all as measure variablesdf$X = rep(newX[,2], 4)
levels(df$variable) = c("0.2", "0.3", "0.4", "0.5")
colnames(df)[1] = "alpha"
ggplot(df, aes(x = X, y = value, col = alpha)) + geom_line() +labs(color=expression(alpha)) +
ylab(expression(rho)) +
xlab(expression(X)) +
theme_bw(base_size=12)+
ggtitle("quadratic")
ggsave("quadratic.png", width=3, height=3)Time comparison
t_la = out$t_la
t_fisher = out$t_fisher
t_lm = out$t_lm
df = data.frame(score = log10(t_lm),
LR = log10(t_fisher),
LA = log10(t_la))
ggplot(melt(df), aes(x=variable, y=value)) +
geom_violin() +
ylab(expression(log[10]~time)) +
xlab("") +
ylim(c(-5, -1)) +
ggtitle("computation time")No id variables; using all as measure variables
sessionInfo()R version 3.5.3 (2019-03-11)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.6
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ggplot2_3.1.0 reshape2_1.4.3 diversitree_0.9-11
[4] ape_5.3
loaded via a namespace (and not attached):
[1] Rcpp_1.0.1 compiler_3.5.3
[3] pillar_1.3.1 git2r_0.25.2
[5] plyr_1.8.4 workflowr_1.2.0
[7] tools_3.5.3 digest_0.6.18
[9] evaluate_0.13 tibble_2.1.1
[11] nlme_3.1-137 gtable_0.3.0
[13] lattice_0.20-38 pkgconfig_2.0.2
[15] rlang_0.3.3 yaml_2.2.0
[17] parallel_3.5.3 xfun_0.5
[19] RcppArmadillo_0.8.600.0.0 withr_2.1.2
[21] stringr_1.4.0 dplyr_0.8.0.1
[23] knitr_1.22 fs_1.2.7
[25] tidyselect_0.2.5 rprojroot_1.3-2
[27] grid_3.5.3 deSolve_1.23
[29] glue_1.3.1 R6_2.4.0
[31] rmarkdown_1.12 purrr_0.3.2
[33] magrittr_1.5 whisker_0.3-2
[35] backports_1.1.3 scales_1.0.0
[37] codetools_0.2-16 htmltools_0.3.6
[39] assertthat_0.2.1 colorspace_1.4-1
[41] labeling_0.3 subplex_1.5-4
[43] stringi_1.4.3 lazyeval_0.2.2
[45] munsell_0.5.0 crayon_1.3.4